K E X I N Li

This study introduces spatial-GPT, a platform for spatial glycan, protein, and transcriptome profiling in human liver tissues, revealing glyco-codes that define disease states and progression.

This paper uses surprisal information-theoretic analysis on spatial transcriptomic data from human glioblastoma to uncover hidden spatial programs and interactions not detected by standard methods.

The paper shows that minimal biophysical constraints can generate a connectome matching a mouse V1 microcircuit and enable a neural network to perform auditory classification.